Articles | Volume 12, issue 13
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Seasonal and interannual variability in wetland methane emissions simulated by CLM4Me' and CAM-chem and comparisons to observations of concentrations
Department of Geography and Environmental and Sustainability Studies Program, Western Michigan University, Kalamazoo, MI 49008, USA
Department of Earth and Atmospheric Sciences, Cornell University, Ithaca, NY 14850, USA
P. G. M. Hess
Department of Earth and Atmospheric Sciences, Cornell University, Ithaca, NY 14850, USA
N. M. Mahowald
Department of Biological and Environmental Engineering, Cornell University, Ithaca, NY 14850, USA
No articles found.
María Gonçalves Ageitos, Vincenzo Obiso, Ron L. Miller, Oriol Jorba, Martina Klose, Matt Dawson, Yves Balkanski, Jan Perlwitz, Sara Basart, Enza Di Tomaso, Jerónimo Escribano, Francesca Macchia, Gilbert Montané, Natalie Mahowald, Robert O. Green, David R. Thompson, and Carlos Pérez García-Pando
Dust aerosols affect our climate differently depending on their mineral composition. We include dust mineralogy in an atmospheric model considering two existing soil maps, which still have large associated uncertainties. The soil data and the distribution of the minerals in different aerosol sizes are key to our model performance. We find significant regional variations in climate-relevant variables, which supports including mineralogy in our current models and the need for improved soil maps.
Longlei Li, Natalie M. Mahowald, Jasper F. Kok, Xiaohong Liu, Mingxuan Wu, Danny M. Leung, Douglas S. Hamilton, Louisa K. Emmons, Yue Huang, Neil Sexton, Jun Meng, and Jessica Wan
Geosci. Model Dev., 15, 8181–8219,Short summary
This study advances mineral dust parameterizations in the Community Atmospheric Model (CAM; version 6.1). Efforts include 1) incorporating a more physically based dust emission scheme; 2) updating the dry deposition scheme; and 3) revising the gravitational settling velocity to account for dust asphericity. Substantial improvements achieved with these updates can help accurately quantify dust–climate interactions using CAM, such as the dust-radiation and dust–cloud interactions.
Danny M. Leung, Jasper F. Kok, Longlei Li, Gregory S. Okin, Catherine Prigent, Martina Klose, Carlos Pérez Garcia-Pando, Laurent Menut, Natalie M. Mahowald, David M. Lawrence, and Marcelo Chamecki
Atmos. Chem. Phys. Discuss.,
Revised manuscript accepted for ACPShort summary
Desert dust modeling is important for understanding climate change, as dust regulates the atmosphere's greenhouse effect and radiation. This study formulates and proposes a more physical and realistic desert dust emission scheme for global and regional climate models. By considering more aeolian processes in our emission scheme, our simulations match better against dust observations than existing schemes. We believe this work is vital in improving dust representation in climate models.
Ye Wang, Natalie Mahowald, Peter Hess, Wenxiu Sun, and Gang Chen
Atmos. Chem. Phys., 22, 7575–7592,Short summary
PM2.5 is positively related to anticyclonic wave activity (AWA) changes close to the observing sites. Changes between current and future climates in AWA can explain up to 75 % of PM2.5 variability at some stations using a linear regression model. Our analysis indicates that higher PM2.5 concentrations occur when a positive AWA anomaly is prominent, which could be critical for understanding how pollutants respond to changing atmospheric circulation and for developing robust pollution projections.
Julius Vira, Peter Hess, Money Ossohou, and Corinne Galy-Lacaux
Atmos. Chem. Phys., 22, 1883–1904,Short summary
Ammonia is one of the main components of nitrogen deposition. Here we use a new model to assess the ammonia emissions from agriculture, the largest anthropogenic source of ammonia. The model results are consistent with earlier estimates over industrialized regions in agreement with observations. However, the model predicts much higher emissions over sub-Saharan Africa compared to earlier estimates. Available observations from surface stations and satellites support these higher emissions.
Jasper F. Kok, Adeyemi A. Adebiyi, Samuel Albani, Yves Balkanski, Ramiro Checa-Garcia, Mian Chin, Peter R. Colarco, Douglas S. Hamilton, Yue Huang, Akinori Ito, Martina Klose, Danny M. Leung, Longlei Li, Natalie M. Mahowald, Ron L. Miller, Vincenzo Obiso, Carlos Pérez García-Pando, Adriana Rocha-Lima, Jessica S. Wan, and Chloe A. Whicker
Atmos. Chem. Phys., 21, 8127–8167,Short summary
Desert dust interacts with virtually every component of the Earth system, including the climate system. We develop a new methodology to represent the global dust cycle that integrates observational constraints on the properties and abundance of desert dust with global atmospheric model simulations. We show that the resulting representation of the global dust cycle is more accurate than what can be obtained from a large number of current climate global atmospheric models.
Jasper F. Kok, Adeyemi A. Adebiyi, Samuel Albani, Yves Balkanski, Ramiro Checa-Garcia, Mian Chin, Peter R. Colarco, Douglas S. Hamilton, Yue Huang, Akinori Ito, Martina Klose, Longlei Li, Natalie M. Mahowald, Ron L. Miller, Vincenzo Obiso, Carlos Pérez García-Pando, Adriana Rocha-Lima, and Jessica S. Wan
Atmos. Chem. Phys., 21, 8169–8193,Short summary
The many impacts of dust on the Earth system depend on dust mineralogy, which varies between dust source regions. We constrain the contribution of the world’s main dust source regions by integrating dust observations with global model simulations. We find that Asian dust contributes more and that North African dust contributes less than models account for. We obtain a dataset of each source region’s contribution to the dust cycle that can be used to constrain dust impacts on the Earth system.
Longlei Li, Natalie M. Mahowald, Ron L. Miller, Carlos Pérez García-Pando, Martina Klose, Douglas S. Hamilton, Maria Gonçalves Ageitos, Paul Ginoux, Yves Balkanski, Robert O. Green, Olga Kalashnikova, Jasper F. Kok, Vincenzo Obiso, David Paynter, and David R. Thompson
Atmos. Chem. Phys., 21, 3973–4005,Short summary
For the first time, this study quantifies the range of the dust direct radiative effect due to uncertainty in the soil mineral abundance using all currently available information. We show that the majority of the estimated direct radiative effect range is due to uncertainty in the simulated mass fractions of iron oxides and thus their soil abundance, which is independent of the model employed. We therefore prove the necessity of considering mineralogy for understanding dust–climate interactions.
Julius Vira, Peter Hess, Jeff Melkonian, and William R. Wieder
Geosci. Model Dev., 13, 4459–4490,Short summary
Mostly emitted by the agricultural sector, ammonia has an important role in atmospheric chemistry. We developed a model to simulate how ammonia emissions respond to changes in temperature and soil moisture, and we evaluated agricultural ammonia emissions globally. The simulated emissions agree with earlier estimates over many regions, but the results highlight the variability of ammonia emissions and suggest that emissions in warm climates may be higher than previously thought.
Wenxiu Sun, Peter Hess, Gang Chen, and Simone Tilmes
Atmos. Chem. Phys., 19, 12917–12933,Short summary
Using both observations and a chemistry climate–model we establish that in most locations changes in the waviness of the 500 hPa flow field, as measured by the local anticyclonic wave activity (AWA), explain a significant fraction of the interannual variability in surface ozone over the United States. In addition, we find that the change in AWA in a future climate (circa 2100) is predicted to cause a change in surface ozone ranging between –6 ppb and 6 ppb.
Douglas S. Hamilton, Rachel A. Scanza, Yan Feng, Joseph Guinness, Jasper F. Kok, Longlei Li, Xiaohong Liu, Sagar D. Rathod, Jessica S. Wan, Mingxuan Wu, and Natalie M. Mahowald
Geosci. Model Dev., 12, 3835–3862,Short summary
MIMI v1.0 was designed for use within Earth system models to simulate the 3-D emission, atmospheric processing, and deposition of iron and its soluble fraction. Understanding the iron cycle is important due to its role as an essential micronutrient for ocean phytoplankton; its supply limits primary productivity in many of the world's oceans. Human activity has perturbed the iron cycle, and MIMI is capable of diagnosing many of these impacts; hence, it is important for future climate studies.
Susan J. Cheng, Peter G. Hess, William R. Wieder, R. Quinn Thomas, Knute J. Nadelhoffer, Julius Vira, Danica L. Lombardozzi, Per Gundersen, Ivan J. Fernandez, Patrick Schleppi, Marie-Cécile Gruselle, Filip Moldan, and Christine L. Goodale
Biogeosciences, 16, 2771–2793,Short summary
Nitrogen deposition and fertilizer can change how much carbon is stored in plants and soils. Understanding how much added nitrogen is recovered in plants or soils is critical to estimating the size of the future land carbon sink. We compared how nitrogen additions are recovered in modeled soil and plant stocks against data from long-term nitrogen addition experiments. We found that the model simulates recovery of added nitrogen into soils through a different process than found in the field.
George S. Fanourgakis, Maria Kanakidou, Athanasios Nenes, Susanne E. Bauer, Tommi Bergman, Ken S. Carslaw, Alf Grini, Douglas S. Hamilton, Jill S. Johnson, Vlassis A. Karydis, Alf Kirkevåg, John K. Kodros, Ulrike Lohmann, Gan Luo, Risto Makkonen, Hitoshi Matsui, David Neubauer, Jeffrey R. Pierce, Julia Schmale, Philip Stier, Kostas Tsigaridis, Twan van Noije, Hailong Wang, Duncan Watson-Parris, Daniel M. Westervelt, Yang Yang, Masaru Yoshioka, Nikos Daskalakis, Stefano Decesari, Martin Gysel-Beer, Nikos Kalivitis, Xiaohong Liu, Natalie M. Mahowald, Stelios Myriokefalitakis, Roland Schrödner, Maria Sfakianaki, Alexandra P. Tsimpidi, Mingxuan Wu, and Fangqun Yu
Atmos. Chem. Phys., 19, 8591–8617,Short summary
Effects of aerosols on clouds are important for climate studies but are among the largest uncertainties in climate projections. This study evaluates the skill of global models to simulate aerosol, cloud condensation nuclei (CCN) and cloud droplet number concentrations (CDNCs). Model results show reduced spread in CDNC compared to CCN due to the negative correlation between the sensitivities of CDNC to aerosol number concentration (air pollution) and updraft velocity (atmospheric dynamics).
Stelios Myriokefalitakis, Akinori Ito, Maria Kanakidou, Athanasios Nenes, Maarten C. Krol, Natalie M. Mahowald, Rachel A. Scanza, Douglas S. Hamilton, Matthew S. Johnson, Nicholas Meskhidze, Jasper F. Kok, Cecile Guieu, Alex R. Baker, Timothy D. Jickells, Manmohan M. Sarin, Srinivas Bikkina, Rachel Shelley, Andrew Bowie, Morgane M. G. Perron, and Robert A. Duce
Biogeosciences, 15, 6659–6684,Short summary
The first atmospheric iron (Fe) deposition model intercomparison is presented in this study, as a result of the deliberations of the United Nations Joint Group of Experts on the Scientific Aspects of Marine Environmental Protection (GESAMP; http://www.gesamp.org/) Working Group 38. We conclude that model diversity over remote oceans reflects uncertainty in the Fe content parameterizations of dust aerosols, combustion aerosol emissions and the size distribution of transported aerosol Fe.
Arlene M. Fiore, Emily V. Fischer, George P. Milly, Shubha Pandey Deolal, Oliver Wild, Daniel A. Jaffe, Johannes Staehelin, Olivia E. Clifton, Dan Bergmann, William Collins, Frank Dentener, Ruth M. Doherty, Bryan N. Duncan, Bernd Fischer, Stefan Gilge, Peter G. Hess, Larry W. Horowitz, Alexandru Lupu, Ian A. MacKenzie, Rokjin Park, Ludwig Ries, Michael G. Sanderson, Martin G. Schultz, Drew T. Shindell, Martin Steinbacher, David S. Stevenson, Sophie Szopa, Christoph Zellweger, and Guang Zeng
Atmos. Chem. Phys., 18, 15345–15361,Short summary
We demonstrate a proof-of-concept approach for applying northern midlatitude mountaintop peroxy acetyl nitrate (PAN) measurements and a multi-model ensemble during April to constrain the influence of continental-scale anthropogenic precursor emissions on PAN. Our findings imply a role for carefully coordinated multi-model ensembles in helping identify observations for discriminating among widely varying (and poorly constrained) model responses of atmospheric constituents to changes in emissions.
Rachel A. Scanza, Douglas S. Hamilton, Carlos Perez Garcia-Pando, Clifton Buck, Alex Baker, and Natalie M. Mahowald
Atmos. Chem. Phys., 18, 14175–14196,Short summary
Soluble iron input to remote oceans from dust and combustion aerosols may significantly impact the ability of the ocean to remove carbon dioxide from the atmosphere. In this paper, the processing of insoluble iron during atmospheric transport is simulated using parameterizations that can be implemented in most Earth system models. Our mechanism reasonably matches observations and is computationally efficient, enabling the study of trends and climate impacts due to the Fe–C cycle.
Pakawat Phalitnonkiat, Peter G. M. Hess, Mircea D. Grigoriu, Gennady Samorodnitsky, Wenxiu Sun, Ellie Beaudry, Simone Tilmes, Makato Deushi, Beatrice Josse, David Plummer, and Kengo Sudo
Atmos. Chem. Phys., 18, 11927–11948,Short summary
The co-occurrence of heat waves and pollution events and the resulting high mortality rates emphasize the importance of the co-occurrence of pollution and temperature extremes. We analyze ozone and temperature extremes and their joint occurrence over the United States during the summer months (JJA) in measurement data and in model simulations of the present and future climates.
Masa Kageyama, Pascale Braconnot, Sandy P. Harrison, Alan M. Haywood, Johann H. Jungclaus, Bette L. Otto-Bliesner, Jean-Yves Peterschmitt, Ayako Abe-Ouchi, Samuel Albani, Patrick J. Bartlein, Chris Brierley, Michel Crucifix, Aisling Dolan, Laura Fernandez-Donado, Hubertus Fischer, Peter O. Hopcroft, Ruza F. Ivanovic, Fabrice Lambert, Daniel J. Lunt, Natalie M. Mahowald, W. Richard Peltier, Steven J. Phipps, Didier M. Roche, Gavin A. Schmidt, Lev Tarasov, Paul J. Valdes, Qiong Zhang, and Tianjun Zhou
Geosci. Model Dev., 11, 1033–1057,Short summary
The Paleoclimate Modelling Intercomparison Project (PMIP) takes advantage of the existence of past climate states radically different from the recent past to test climate models used for climate projections and to better understand these climates. This paper describes the PMIP contribution to CMIP6 (Coupled Model Intercomparison Project, 6th phase) and possible analyses based on PMIP results, as well as on other CMIP6 projects.
Bette L. Otto-Bliesner, Pascale Braconnot, Sandy P. Harrison, Daniel J. Lunt, Ayako Abe-Ouchi, Samuel Albani, Patrick J. Bartlein, Emilie Capron, Anders E. Carlson, Andrea Dutton, Hubertus Fischer, Heiko Goelzer, Aline Govin, Alan Haywood, Fortunat Joos, Allegra N. LeGrande, William H. Lipscomb, Gerrit Lohmann, Natalie Mahowald, Christoph Nehrbass-Ahles, Francesco S. R. Pausata, Jean-Yves Peterschmitt, Steven J. Phipps, Hans Renssen, and Qiong Zhang
Geosci. Model Dev., 10, 3979–4003,Short summary
The PMIP4 and CMIP6 mid-Holocene and Last Interglacial simulations provide an opportunity to examine the impact of two different changes in insolation forcing on climate at times when other forcings were relatively similar to present. This will allow exploration of the role of feedbacks relevant to future projections. Evaluating these simulations using paleoenvironmental data will provide direct out-of-sample tests of the reliability of state-of-the-art models to simulate climate changes.
Masa Kageyama, Samuel Albani, Pascale Braconnot, Sandy P. Harrison, Peter O. Hopcroft, Ruza F. Ivanovic, Fabrice Lambert, Olivier Marti, W. Richard Peltier, Jean-Yves Peterschmitt, Didier M. Roche, Lev Tarasov, Xu Zhang, Esther C. Brady, Alan M. Haywood, Allegra N. LeGrande, Daniel J. Lunt, Natalie M. Mahowald, Uwe Mikolajewicz, Kerim H. Nisancioglu, Bette L. Otto-Bliesner, Hans Renssen, Robert A. Tomas, Qiong Zhang, Ayako Abe-Ouchi, Patrick J. Bartlein, Jian Cao, Qiang Li, Gerrit Lohmann, Rumi Ohgaito, Xiaoxu Shi, Evgeny Volodin, Kohei Yoshida, Xiao Zhang, and Weipeng Zheng
Geosci. Model Dev., 10, 4035–4055,Short summary
The Last Glacial Maximum (LGM, 21000 years ago) is an interval when global ice volume was at a maximum, eustatic sea level close to a minimum, greenhouse gas concentrations were lower, atmospheric aerosol loadings were higher than today, and vegetation and land-surface characteristics were different from today. This paper describes the implementation of the LGM numerical experiment for the PMIP4-CMIP6 modelling intercomparison projects and the associated sensitivity experiments.
Molly B. Smith, Natalie M. Mahowald, Samuel Albani, Aaron Perry, Remi Losno, Zihan Qu, Beatrice Marticorena, David A. Ridley, and Colette L. Heald
Atmos. Chem. Phys., 17, 3253–3278,Short summary
Using different meteorology reanalyses to drive dust in climate modeling can produce dissimilar global dust distributions, especially in the Southern Hemisphere (SH). It may therefore not be advisable for SH dust studies to base results on simulations driven by one reanalysis. Northern Hemisphere dust varies mostly on seasonal timescales, while SH dust varies on interannual timescales. Dust is an important part of climate modeling, and we hope this contributes to understanding these simulations.
Bette L. Otto-Bliesner, Pascale Braconnot, Sandy P. Harrison, Daniel J. Lunt, Ayako Abe-Ouchi, Samuel Albani, Patrick J. Bartlein, Emilie Capron, Anders E. Carlson, Andrea Dutton, Hubertus Fischer, Heiko Goelzer, Aline Govin, Alan Haywood, Fortunat Joos, Allegra N. Legrande, William H. Lipscomb, Gerrit Lohmann, Natalie Mahowald, Christoph Nehrbass-Ahles, Jean-Yves Peterschmidt, Francesco S.-R. Pausata, Steven Phipps, and Hans Renssen
Clim. Past Discuss.,
Robert Raiswell, Jon R. Hawkings, Liane G. Benning, Alex R. Baker, Ros Death, Samuel Albani, Natalie Mahowald, Michael D. Krom, Simon W. Poulton, Jemma Wadham, and Martyn Tranter
Biogeosciences, 13, 3887–3900,Short summary
Iron is an essential nutrient for plankton growth. One important source of iron is wind-blown dust. The polar oceans are remote from dust sources but melting icebergs supply sediment that contains iron which is potentially available to plankton. We show that iceberg sediments contain more potentially bioavailable iron than wind-blown dust. Iceberg sources will become increasingly important with climate change and increased plankton growth can remove more carbon dioxide from the atmosphere.
Stuart Riddick, Daniel Ward, Peter Hess, Natalie Mahowald, Raia Massad, and Elisabeth Holland
Biogeosciences, 13, 3397–3426,Short summary
Future increases are predicted in the amount of nitrogen produced as manure or used as synthetic fertilizer in agriculture. However, the impact of climate on the subsequent fate of this nitrogen has not been evaluated. Here we describe, analyze and evaluate the FAN (flows of agricultural nitrogen) process model that simulates the the climate-dependent flows of nitrogen from agriculture. The FAN model is suitable for use within a global terrestrial climate model.
Natalie Mahowald, Fiona Lo, Yun Zheng, Laura Harrison, Chris Funk, Danica Lombardozzi, and Christine Goodale
Earth Syst. Dynam., 7, 211–229,Short summary
This paper evaluates the model predictions of leaf area index in the current climate, compared against satellite observations. It also summarizes the predicted changes in leaf area index in the future, and identifies whether some of the uncertainty in future predictions can be decreased.
J. Müller, R. Paudel, C. A. Shoemaker, J. Woodbury, Y. Wang, and N. Mahowald
Geosci. Model Dev., 8, 3285–3310,Short summary
We tune the CH4-related parameters of the Community Land Model (CLM) using surrogate global optimization in order to reduce the discrepancies between the CLM predictions and observed CH4 emissions. This is the first application of a surrogate optimization method to calibrate a global climate model. We found that the observation data drives the model to predict more CH4 emissions in the northern latitudes and less in the tropics.
Y. Zhang, N. Mahowald, R. A. Scanza, E. Journet, K. Desboeufs, S. Albani, J. F. Kok, G. Zhuang, Y. Chen, D. D. Cohen, A. Paytan, M. D. Patey, E. P. Achterberg, J. P. Engelbrecht, and K. W. Fomba
Biogeosciences, 12, 5771–5792,Short summary
A new technique to determine a size-fractionated global soil elemental emission inventory based on a global soil and mineralogical data set is introduced. Spatial variability of mineral dust elemental fractions (8 elements, e.g., Ca, Fe, Al) is identified on a global scale, particularly for Ca. The Ca/Al ratio ranged between 0.1 and 5.0 and is confirmed as an indicator of dust source regions by a global dust model. Total and soluble dust element fluxes into different ocean basins are estimated.
S. Albani, N. M. Mahowald, G. Winckler, R. F. Anderson, L. I. Bradtmiller, B. Delmonte, R. François, M. Goman, N. G. Heavens, P. P. Hesse, S. A. Hovan, S. G. Kang, K. E. Kohfeld, H. Lu, V. Maggi, J. A. Mason, P. A. Mayewski, D. McGee, X. Miao, B. L. Otto-Bliesner, A. T. Perry, A. Pourmand, H. M. Roberts, N. Rosenbloom, T. Stevens, and J. Sun
Clim. Past, 11, 869–903,Short summary
We propose an innovative framework to organize paleodust records, formalized in a publicly accessible database, and discuss the emerging properties of the global dust cycle during the Holocene by integrating our analysis with simulations performed with the Community Earth System Model. We show how the size distribution of dust is intrinsically related to the dust mass accumulation rates and that only considering a consistent size range allows for a consistent analysis of the global dust cycle.
D. S. Ward and N. M. Mahowald
Earth Syst. Dynam., 6, 175–194,Short summary
The radiative forcing of land use and land cover change activities has recently been computed for a set of forcing agents including long-lived greenhouse gases, short-lived agents (ozone and aerosols), and land surface albedo change. Here we address where the global forcing comes from and what land use activities, such as deforestation or agriculture, contribute the most forcing. We find that changes in forest and crop area can be used to predict the land use radiative forcing in some regions.
P. Hess, D. Kinnison, and Q. Tang
Atmos. Chem. Phys., 15, 2341–2365,Short summary
Using a series of model simulations, we find that at widespread NH extratropical locations, interannual tropospheric ozone variability is largely determined by the transport of ozone from the stratosphere. This has implications in the interpretation of measured tropospheric ozone variability in light of changes in the emissions of ozone precursors and in the response of tropospheric ozone to climate change.
R. A. Scanza, N. Mahowald, S. Ghan, C. S. Zender, J. F. Kok, X. Liu, Y. Zhang, and S. Albani
Atmos. Chem. Phys., 15, 537–561,Short summary
The main purpose of this study was to build a framework in the Community Atmosphere Models version 4 and 5 within the Community Earth System Model to simulate dust aerosols as their component minerals. With this framework, we investigate the direct radiative forcing that results from the mineral speciation. We find that adding mineralogy results in a small positive forcing at the top of the atmosphere, while simulations without mineralogy have a small negative forcing.
J. F. Kok, N. M. Mahowald, G. Fratini, J. A. Gillies, M. Ishizuka, J. F. Leys, M. Mikami, M.-S. Park, S.-U. Park, R. S. Van Pelt, and T. M. Zobeck
Atmos. Chem. Phys., 14, 13023–13041,Short summary
We developed an improved model for the emission of dust particulates ("aerosols") emitted by wind erosion from the world's deserts. The implementation of our improved dust emission model into a climate model improves its agreement against measurements. We furthermore find that dust emissions are substantially more sensitive to the soil state than most current climate models account for.
D. S. Ward, N. M. Mahowald, and S. Kloster
Atmos. Chem. Phys., 14, 12701–12724,Short summary
While climate change mitigation policy often focuses on the energy sector, we find that 40% of the historical human-caused change in the Earth’s radiative balance can be attributed to land use activities, such as deforestation and agriculture. Since pressure on land resources is expected to increase, we compute a theoretical upper bound on the radiative balance impacts from future land use which suggests that both energy policy and land policy are necessary to minimize future climate change.
W. Sun, P. Hess, and B. Tian
Atmos. Chem. Phys., 14, 11775–11790,
B. Foereid, D. S. Ward, N. Mahowald, E. Paterson, and J. Lehmann
Earth Syst. Dynam., 5, 211–221,
S. K. Clark, D. S. Ward, and N. M. Mahowald
Atmos. Chem. Phys. Discuss.,
Revised manuscript not accepted
D. A. Belikov, S. Maksyutov, M. Krol, A. Fraser, M. Rigby, H. Bian, A. Agusti-Panareda, D. Bergmann, P. Bousquet, P. Cameron-Smith, M. P. Chipperfield, A. Fortems-Cheiney, E. Gloor, K. Haynes, P. Hess, S. Houweling, S. R. Kawa, R. M. Law, Z. Loh, L. Meng, P. I. Palmer, P. K. Patra, R. G. Prinn, R. Saito, and C. Wilson
Atmos. Chem. Phys., 13, 1093–1114,
L. K. Emmons, P. G. Hess, J.-F. Lamarque, and G. G. Pfister
Geosci. Model Dev., 5, 1531–1542,
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Veronika Kronnäs, Klas Lucander, Giuliana Zanchi, Nadja Stadlinger, Salim Belyazid, and Cecilia Akselsson
Biogeosciences, 20, 1879–1899,Short summary
In a future climate, extreme droughts might become more common. Climate change and droughts can have negative effects on soil weathering and plant health. In this study, climate change effects on weathering were studied on sites in Sweden using the model ForSAFE, a climate change scenario and an extreme drought scenario. The modelling shows that weathering is higher during summer and increases with global warming but that weathering during drought summers can become as low as winter weathering.
Agustín Sarquis and Carlos A. Sierra
Biogeosciences, 20, 1759–1771,Short summary
Although plant litter is chemically and physically heterogenous and undergoes multiple transformations, models that represent litter dynamics often ignore this complexity. We used a multi-model inference framework to include information content in litter decomposition datasets and studied the time it takes for litter to decompose as measured by the transit time. In arid lands, the median transit time of litter is about 3 years and has a negative correlation with mean annual temperature.
Qi Guan, Jing Tang, Lian Feng, Stefan Olin, and Guy Schurgers
Biogeosciences, 20, 1635–1648,Short summary
Understanding terrestrial sources of nitrogen is vital to examine lake eutrophication changes. Combining process-based ecosystem modeling and satellite observations, we found that land-leached nitrogen in the Yangtze Plain significantly increased from 1979 to 2018, and terrestrial nutrient sources were positively correlated with eutrophication trends observed in most lakes, demonstrating the necessity of sustainable nitrogen management to control eutrophication.
Vivek K. Arora, Christian Seiler, Libo Wang, and Sian Kou-Giesbrecht
Biogeosciences, 20, 1313–1355,Short summary
The behaviour of natural systems is now very often represented through mathematical models. These models represent our understanding of how nature works. Of course, nature does not care about our understanding. Since our understanding is not perfect, evaluating models is challenging, and there are uncertainties. This paper illustrates this uncertainty for land models and argues that evaluating models in light of the uncertainty in various components provides useful information.
Benjamin S. Felzer
Biogeosciences, 20, 573–587,Short summary
The future of the terrestrial carbon sink depends upon the legacy of past land use, which determines the stand age of the forest and nutrient levels in the soil, both of which affect vegetation growth. This study uses a modeling approach to determine the effects of land-use legacy in the conterminous US from 1750 to 2099. Not accounting for land legacy results in a low carbon sink and high biomass, while water variables are not as highly affected.
Bailu Zhao and Qianlai Zhuang
Biogeosciences, 20, 251–270,Short summary
In this study, we use a process-based model to simulate the northern peatland's C dynamics in response to future climate change during 1990–2300. Northern peatlands are projected to be a C source under all climate scenarios except for the mildest one before 2100 and C sources under all scenarios afterwards. We find northern peatlands are a C sink until pan-Arctic annual temperature reaches −2.09 to −2.89 °C. This study emphasizes the vulnerability of northern peatlands to climate change.
Lin Yu, Silvia Caldararu, Bernhard Ahrens, Thomas Wutzler, Marion Schrumpf, Julian Helfenstein, Chiara Pistocchi, and Sönke Zaehle
Biogeosciences, 20, 57–73,Short summary
In this study, we addressed a key weakness in current ecosystem models regarding the phosphorus exchange in the soil and developed a new scheme to describe this process. We showed that the new scheme improved the model performance for plant productivity, soil organic carbon, and soil phosphorus content at five beech forest sites in Germany. We claim that this new model could be used as a better tool to study ecosystems under future climate change, particularly phosphorus-limited systems.
Alexander J. Norton, A. Anthony Bloom, Nicholas C. Parazoo, Paul A. Levine, Shuang Ma, Renato K. Braghiere, and Luke T. Smallman
This study explores how the representation of leaf phenology affects our ability to predict changes to the carbon balance of land ecosystems. We calibrate a new leaf phenology model against a diverse range of observations at six forest sites, showing that it improves the predictive capability of the processes underlying the ecosystem carbon balance. We then show how changes in temperature and rainfall affect the ecosystem carbon balance with this new model.
Bimal K. Bhattacharya, Kaniska Mallick, Devansh Desai, Ganapati S. Bhat, Ross Morrison, Jamie R. Clevery, William Woodgate, Jason Beringer, Kerry Cawse-Nicholson, Siyan Ma, Joseph Verfaillie, and Dennis Baldocchi
Biogeosciences, 19, 5521–5551,Short summary
Evaporation retrieval in heterogeneous ecosystems is challenging due to empirical estimation of ground heat flux and complex parameterizations of conductances. We developed a parameter-sparse coupled ground heat flux-evaporation model and tested it across different limits of water stress and vegetation fraction in the Northern/Southern Hemisphere. The model performed particularly well in the savannas and showed good potential for evaporative stress monitoring from thermal infrared satellites.
Ara Cho, Linda M. J. Kooijmans, Kukka-Maaria Kohonen, Richard Wehr, and Maarten C. Krol
Carbonyl Sulfide (COS) is a useful constraint on photosynthesis. To simulate COS leaf flux better in the SiB4 model, we propose a new temperature function for the enzyme carbonic anhydrase (CA) and optimize conductances using observations. CA has an optimum temperature below 40 °C, which can be influenced critically by air temperature changes. It brings tropics a smaller and higher latitudes a larger uptake. This update helps resolve gaps in the COS budget identified in earlier studies.
Jie Zhang, Wenxin Zhang, Per-Erik Jansson, and Søren O. Petersen
Biogeosciences, 19, 4811–4832,Short summary
In this study, we relied on a properly controlled laboratory experiment to test the model’s capability of simulating the dominant microbial processes and the emissions of one greenhouse gas (nitrous oxide, N2O) from agricultural soils. This study reveals important processes and parameters that regulate N2O emissions in the investigated model framework and also suggests future steps of model development, which have implications on the broader communities of ecosystem modelers.
Libo Wang, Vivek K. Arora, Paul Bartlett, Ed Chan, and Salvatore R. Curasi
Plant functional types (PFTs) are groups of plant species used to represent vegetation distribution in land surface models. There are large uncertainties associated with existing methods for mapping land cover datasets to PFTs. This study demonstrates how fine-resolution tree cover fraction and land cover datasets can be used to inform the PFT mapping process and reduce the uncertainties. The proposed largely objective method makes it easier to implement new land cover products in models.
Yunyao Ma, Bettina Weber, Alexandra Kratz, José Raggio, Claudia Colesie, Maik Veste, Maaike Y. Bader, and Philipp Porada
Revised manuscript accepted for BGShort summary
Our study found while air temperature, ambient CO2 concentration, light intensity, and relative humidity are key drivers for annual carbon (C) balance, their relative impacts vary markedly among climatic zones. Moreover, seasonal acclimation may alter the C balance substantially at humid sites. Our study implies that climate change may have large effects on biocrust C balance at global scale, and suggests covering different seasons when measuring physiological traits to account for acclimation.
Jan De Pue, José Miguel Barrios, Liyang Liu, Philippe Ciais, Alirio Arboleda, Rafiq Hamdi, Manuela Balzarolo, Fabienne Maignan, and Françoise Gellens-Meulenberghs
Biogeosciences, 19, 4361–4386,Short summary
The functioning of ecosystems involves numerous biophysical processes which interact with each other. Land surface models (LSMs) are used to describe these processes and form an essential component of climate models. In this paper, we evaluate the performance of three LSMs and their interactions with soil moisture and vegetation. Though we found room for improvement in the simulation of soil moisture and drought stress, the main cause of errors was related to the simulated growth of vegetation.
Jarmo Mäkelä, Laura Arppe, Hannu Fritze, Jussi Heinonsalo, Kristiina Karhu, Jari Liski, Markku Oinonen, Petra Straková, and Toni Viskari
Biogeosciences, 19, 4305–4313,Short summary
Soils account for the largest share of carbon found in terrestrial ecosystems, and accurate depiction of soil carbon decomposition is essential in understanding how permanent these carbon storages are. We present a straightforward way to include carbon isotope concentrations into soil decomposition and carbon storages for the Yasso model, which enables the model to use 13C as a natural tracer to track changes in the underlying soil organic matter decomposition.
Ivan Cornut, Nicolas Delpierre, Jean-Paul Laclau, Joannès Guillemot, Yann Nouvellon, Otavio Campoe, Jose Luiz Stape, Vitoria Fernanda Santos, and Guerric le Maire
Potassium is an essential element for living organisms. Trees are dependent upon this element for certain of their functions that allow them to build their trunk using carbon dioxide. Using data from experiments in eucalypt plantations in Brazil and a simplified computer model of the plantations we were able to investigate the effect the lack of potassium can have on the production of wood. Understanding nutrient cycles is useful to understand the response of forests to environmental change.
Ivan Cornut, Guerric le Maire, Jean-Paul Laclau, Joannès Guillemot, Yann Nouvellon, and Nicolas Delpierre
After simulating the effects of low levels of Potassium on the canopy of trees and the uptake of carbon dioxide from the atmosphere by leaves in part 1, here we tried to simulate the way the trees use the carbon they have acquired and the interaction with the potassium cycle in the tree. We show that the effect of low potassium on the efficiency of the trees to acquire carbon is enought to exlplain why they do not produce enough wood when they are in soils with low levels of potassium.
Vasileios Myrgiotis, Thomas Luke Smallman, and Mathew Williams
Biogeosciences, 19, 4147–4170,Short summary
This study shows that livestock grazing and grass cutting can determine whether a grassland is adding (source) or removing (sink) carbon (C) to/from the atmosphere. The annual C balance of 1855 managed grassland fields in Great Britain was quantified for 2017–2018 using process modelling and earth observation data. The examined fields were, on average, small C sinks, but the summer drought of 2018 led to a 9-fold increase in the number of fields that became C sources in 2018 compared to 2017.
J. Robert Logan, Kathe E. Todd-Brown, Kathryn M. Jacobson, Peter J. Jacobson, Roland Vogt, and Sarah E. Evans
Biogeosciences, 19, 4129–4146,Short summary
Understanding how plants decompose is important for understanding where the atmospheric CO2 they absorb ends up after they die. In forests, decomposition is controlled by rain but not in deserts. We performed a 2.5-year study in one of the driest places on earth (the Namib desert in southern Africa) and found that fog and dew, not rainfall, closely controlled how quickly plants decompose. We also created a model to help predict decomposition in drylands with lots of fog and/or dew.
Kevin R. Wilcox, Scott L. Collins, Alan K. Knapp, William Pockman, Zheng Shi, Melinda Smith, and Yiqi Luo
Revised manuscript accepted for BGShort summary
The capacity for carbon storage (C capacity) is an attribute that determines how ecosystems will store carbon in the future. Here, we employ novel data-model integration techniques to identify the carbon capacity of six grassland sites spanning the US Great Plains. Hot and dry sites had low C capacity due to less plant growth and high turnover of soil C so they may be a C source in the future. Alternately, cooler and wetter ecosystems had high C capacity, so these systems may be a future C sink.
Carlos A. Sierra, Verónika Ceballos-Núñez, Henrik Hartmann, David Herrera-Ramírez, and Holger Metzler
Biogeosciences, 19, 3727–3738,Short summary
Empirical work that estimates the age of respired CO2 from vegetation tissue shows that it may take from years to decades to respire previously produced photosynthates. However, many ecosystem models represent respiration processes in a form that cannot reproduce these observations. In this contribution, we attempt to provide compelling evidence, based on recent research, with the aim to promote a change in the predominant paradigm implemented in ecosystem models.
César Dionisio Jiménez-Rodríguez, Mauro Sulis, and Stanislaus Schymanski
Biogeosciences, 19, 3395–3423,Short summary
Vegetation relies on soil water reservoirs during dry periods. However, when this source is depleted, the plants may access water stored deeper in the rocks. This rock moisture contribution is usually omitted in large-scale models, which affects modeled plant water use during dry periods. Our study illustrates that including this additional source of water in the Community Land Model improves the model's ability to reproduce observed plant water use at seasonally dry sites.
Marco Carozzi, Raphaël Martin, Katja Klumpp, and Raia Silvia Massad
Biogeosciences, 19, 3021–3050,Short summary
Crop and grassland production indicates a strong reduction due to the shortening of the length of the growing cycle associated with rising temperatures. Greenhouse gas emissions will increase exponentially over the century, often exceeding the CO2 accumulation of agro-ecosystems. Water demand will double in the next few decades, whereas the benefits in terms of yield will not fill the gap of C losses due to climate perturbation. Climate change will have a regionally distributed effect in the EU.
Anthony Mucia, Bertrand Bonan, Clément Albergel, Yongjun Zheng, and Jean-Christophe Calvet
Biogeosciences, 19, 2557–2581,Short summary
For the first time, microwave vegetation optical depth data are assimilated in a land surface model in order to analyze leaf area index and root zone soil moisture. The advantage of microwave products is the higher observation frequency. A large variety of independent datasets are used to verify the added value of the assimilation. It is shown that the assimilation is able to improve the representation of soil moisture, vegetation conditions, and terrestrial water and carbon fluxes.
Camille Abadie, Fabienne Maignan, Marine Remaud, Jérôme Ogée, J. Elliott Campbell, Mary E. Whelan, Florian Kitz, Felix M. Spielmann, Georg Wohlfahrt, Richard Wehr, Wu Sun, Nina Raoult, Ulli Seibt, Didier Hauglustaine, Sinikka T. Lennartz, Sauveur Belviso, David Montagne, and Philippe Peylin
Biogeosciences, 19, 2427–2463,Short summary
A better constraint of the components of the carbonyl sulfide (COS) global budget is needed to exploit its potential as a proxy of gross primary productivity. In this study, we compare two representations of oxic soil COS fluxes, and we develop an approach to represent anoxic soil COS fluxes in a land surface model. We show the importance of atmospheric COS concentration variations on oxic soil COS fluxes and provide new estimates for oxic and anoxic soil contributions to the COS global budget.
Jianyong Ma, Sam S. Rabin, Peter Anthoni, Anita D. Bayer, Sylvia S. Nyawira, Stefan Olin, Longlong Xia, and Almut Arneth
Biogeosciences, 19, 2145–2169,Short summary
Improved agricultural management plays a vital role in protecting soils from degradation in eastern Africa. We simulated the impacts of seven management practices on soil carbon pools, nitrogen loss, and crop yield under different climate scenarios in this region. This study highlights the possibilities of conservation agriculture when targeting long-term environmental sustainability and food security in crop ecosystems, particularly for those with poor soil conditions in tropical climates.
Elisabeth Tschumi, Sebastian Lienert, Karin van der Wiel, Fortunat Joos, and Jakob Zscheischler
Biogeosciences, 19, 1979–1993,Short summary
Droughts and heatwaves are expected to occur more often in the future, but their effects on land vegetation and the carbon cycle are poorly understood. We use six climate scenarios with differing extreme occurrences and a vegetation model to analyse these effects. Tree coverage and associated plant productivity increase under a climate with no extremes. Frequent co-occurring droughts and heatwaves decrease plant productivity more than the combined effects of single droughts or heatwaves.
Jennifer A. Holm, David M. Medvigy, Benjamin Smith, Jeffrey S. Dukes, Claus Beier, Mikhail Mishurov, Xiangtao Xu, Jeremy W. Lichstein, Craig D. Allen, Klaus S. Larsen, Yiqi Luo, Cari Ficken, William T. Pockman, William R. L. Anderegg, and Anja Rammig
Revised manuscript accepted for BGShort summary
Unprecedented climate extremes (UCEs) are expected to have dramatic impacts for ecosystems. We examine extreme droughts with rising CO2 and temperatures using two dynamic vegetation models, to assess ecological processes to measure, and reduce model uncertainties. The models predict strong nonlinear responses to UCEs. Due to different model representations, the models differ in magnitude and trajectory of forest loss. Therefore, we explored specific plant responses that reflect knowledge gaps.
Stephanie G. Stettz, Nicholas C. Parazoo, A. Anthony Bloom, Peter D. Blanken, David R. Bowling, Sean P. Burns, Cédric Bacour, Fabienne Maignan, Brett Raczka, Alexander J. Norton, Ian Baker, Mathew Williams, Mingjie Shi, Yongguang Zhang, and Bo Qiu
Biogeosciences, 19, 541–558,Short summary
Uncertainty in the response of photosynthesis to temperature poses a major challenge to predicting the response of forests to climate change. In this paper, we study how photosynthesis in a mountainous evergreen forest is limited by temperature. This study highlights that cold temperature is a key factor that controls spring photosynthesis. Including the cold-temperature limitation in an ecosystem model improved its ability to simulate spring photosynthesis.
Eva Kanari, Lauric Cécillon, François Baudin, Hugues Clivot, Fabien Ferchaud, Sabine Houot, Florent Levavasseur, Bruno Mary, Laure Soucémarianadin, Claire Chenu, and Pierre Barré
Biogeosciences, 19, 375–387,Short summary
Soil organic carbon (SOC) is crucial for climate regulation, soil quality, and food security. Predicting its evolution over the next decades is key for appropriate land management policies. However, SOC projections lack accuracy. Here we show for the first time that PARTYSOC, an approach combining thermal analysis and machine learning optimizes the accuracy of SOC model simulations at independent sites. This method can be applied at large scales, improving SOC projections on a continental scale.
Linda M. J. Kooijmans, Ara Cho, Jin Ma, Aleya Kaushik, Katherine D. Haynes, Ian Baker, Ingrid T. Luijkx, Mathijs Groenink, Wouter Peters, John B. Miller, Joseph A. Berry, Jerome Ogée, Laura K. Meredith, Wu Sun, Kukka-Maaria Kohonen, Timo Vesala, Ivan Mammarella, Huilin Chen, Felix M. Spielmann, Georg Wohlfahrt, Max Berkelhammer, Mary E. Whelan, Kadmiel Maseyk, Ulli Seibt, Roisin Commane, Richard Wehr, and Maarten Krol
Biogeosciences, 18, 6547–6565,Short summary
The gas carbonyl sulfide (COS) can be used to estimate photosynthesis. To adopt this approach on regional and global scales, we need biosphere models that can simulate COS exchange. So far, such models have not been evaluated against observations. We evaluate the COS biosphere exchange of the SiB4 model against COS flux observations. We find that the model is capable of simulating key processes in COS biosphere exchange. Still, we give recommendations for further improvement of the model.
Alexandra Pongracz, David Wårlind, Paul A. Miller, and Frans-Jan W. Parmentier
Biogeosciences, 18, 5767–5787,Short summary
This study shows that the introduction of a multi-layer snow scheme in the LPJ-GUESS DGVM improved simulations of high-latitude soil temperature dynamics and permafrost extent compared to observations. In addition, these improvements led to shifts in carbon fluxes that contrasted within and outside of the permafrost region. Our results show that a realistic snow scheme is essential to accurately simulate snow–soil–vegetation relationships and carbon–climate feedbacks.
Chris H. Wilson and Stefan Gerber
Biogeosciences, 18, 5669–5679,Short summary
To better mitigate against climate change, it is imperative that ecosystem scientists understand how microbes decompose organic carbon in the soil and thereby release it as carbon dioxide into the atmosphere. A major challenge is the high variability across ecosystems in microbial biomass and in the environmental factors like temperature that drive their activity. In this paper, we use math to better understand how this variability impacts carbon dioxide release over large scales.
Andrew H. MacDougall
Biogeosciences, 18, 4937–4952,Short summary
Permafrost soils hold about twice as much carbon as the atmosphere. As the Earth warms the organic matter in these soils will decay, releasing CO2 and CH4. It is expected that these soils will continue to release carbon to the atmosphere long after man-made emissions of greenhouse gases cease. Here we use a method employing hundreds of slightly varying model versions to estimate how much warming permafrost carbon will cause after human emissions of CO2 end.
Wei Zhang, Zhisheng Yao, Siqi Li, Xunhua Zheng, Han Zhang, Lei Ma, Kai Wang, Rui Wang, Chunyan Liu, Shenghui Han, Jia Deng, and Yong Li
Biogeosciences, 18, 4211–4225,Short summary
The hydro-biogeochemical model Catchment Nutrient Management Model – DeNitrification-DeComposition (CNMM-DNDC) is improved by incorporating a soil thermal module to simulate the soil thermal regime in the presence of freeze–thaw cycles. The modified model is validated at a seasonally frozen catchment with typical alpine ecosystems (wetland, meadow and forest). The simulated aggregate emissions of methane and nitrous oxide are highest for the wetland, which is dominated by the methane emissions.
Sian Kou-Giesbrecht, Sergey Malyshev, Isabel Martínez Cano, Stephen W. Pacala, Elena Shevliakova, Thomas A. Bytnerowicz, and Duncan N. L. Menge
Biogeosciences, 18, 4143–4183,Short summary
Representing biological nitrogen fixation (BNF) is an important challenge for land models. We present a novel representation of BNF and updated nitrogen cycling in a land model. It includes a representation of asymbiotic BNF by soil microbes and the competitive dynamics between nitrogen-fixing and non-fixing plants. It improves estimations of major carbon and nitrogen pools and fluxes and their temporal dynamics in comparison to previous representations of BNF in land models.
Christopher R. Taylor, Victoria Janes-Bassett, Gareth K. Phoenix, Ben Keane, Iain P. Hartley, and Jessica A. C. Davies
Biogeosciences, 18, 4021–4037,Short summary
We used experimental data to model two phosphorus-limited grasslands and investigated their response to nitrogen (N) deposition. Greater uptake of organic P facilitated a positive response to N deposition, stimulating growth and soil carbon storage. Where organic P access was less, N deposition exacerbated P demand and reduced plant C input to the soil. This caused more C to be released into the atmosphere than is taken in, reducing the climate-mitigation capacity of the modelled grassland.
Jonathan Barichivich, Philippe Peylin, Thomas Launois, Valerie Daux, Camille Risi, Jina Jeong, and Sebastiaan Luyssaert
Biogeosciences, 18, 3781–3803,Short summary
The width and the chemical signals of tree rings have the potential to test and improve the physiological responses simulated by global land surface models, which are at the core of future climate projections. Here, we demonstrate the novel use of tree-ring width and carbon and oxygen stable isotopes to evaluate the representation of tree growth and physiology in a global land surface model at temporal scales beyond experimentation and direct observation.
Gesa Meyer, Elyn R. Humphreys, Joe R. Melton, Alex J. Cannon, and Peter M. Lafleur
Biogeosciences, 18, 3263–3283,Short summary
Shrub and sedge plant functional types (PFTs) were incorporated in the land surface component of the Canadian Earth System Model to improve representation of Arctic tundra ecosystems. Evaluated against 14 years of non-winter measurements, the magnitude and seasonality of carbon dioxide and energy fluxes at a Canadian dwarf-shrub tundra site were better captured by the shrub PFTs than by previously used grass and tree PFTs. Model simulations showed the tundra site to be an annual net CO2 source.
Martina Franz and Sönke Zaehle
Biogeosciences, 18, 3219–3241,Short summary
The combined effects of ozone and nitrogen deposition on the terrestrial carbon uptake and storage has been unclear. Our simulations, from 1850 to 2099, show that ozone-related damage considerably reduced gross primary production and carbon storage in the past. The growth-stimulating effect induced by nitrogen deposition is offset until the 2050s. Accounting for nitrogen deposition without considering ozone effects might lead to an overestimation of terrestrial carbon uptake and storage.
Fabienne Maignan, Camille Abadie, Marine Remaud, Linda M. J. Kooijmans, Kukka-Maaria Kohonen, Róisín Commane, Richard Wehr, J. Elliott Campbell, Sauveur Belviso, Stephen A. Montzka, Nina Raoult, Ulli Seibt, Yoichi P. Shiga, Nicolas Vuichard, Mary E. Whelan, and Philippe Peylin
Biogeosciences, 18, 2917–2955,Short summary
The assimilation of carbonyl sulfide (COS) by continental vegetation has been proposed as a proxy for gross primary production (GPP). Using a land surface and a transport model, we compare a mechanistic representation of the plant COS uptake (Berry et al., 2013) to the classical leaf relative uptake (LRU) approach linking GPP and vegetation COS fluxes. We show that at high temporal resolutions a mechanistic approach is mandatory, but at large scales the LRU approach compares similarly.
Caroline A. Famiglietti, T. Luke Smallman, Paul A. Levine, Sophie Flack-Prain, Gregory R. Quetin, Victoria Meyer, Nicholas C. Parazoo, Stephanie G. Stettz, Yan Yang, Damien Bonal, A. Anthony Bloom, Mathew Williams, and Alexandra G. Konings
Biogeosciences, 18, 2727–2754,Short summary
Model uncertainty dominates the spread in terrestrial carbon cycle predictions. Efforts to reduce it typically involve adding processes, thereby increasing model complexity. However, if and how model performance scales with complexity is unclear. Using a suite of 16 structurally distinct carbon cycle models, we find that increased complexity only improves skill if parameters are adequately informed. Otherwise, it can degrade skill, and an intermediate-complexity model is optimal.
Gilvan Sampaio, Marília H. Shimizu, Carlos A. Guimarães-Júnior, Felipe Alexandre, Marcelo Guatura, Manoel Cardoso, Tomas F. Domingues, Anja Rammig, Celso von Randow, Luiz F. C. Rezende, and David M. Lapola
Biogeosciences, 18, 2511–2525,Short summary
The impact of large-scale deforestation and the physiological effects of elevated atmospheric CO2 on Amazon rainfall are systematically compared in this study. Our results are remarkable in showing that the two disturbances cause equivalent rainfall decrease, though through different causal mechanisms. These results highlight the importance of not only curbing regional deforestation but also reducing global CO2 emissions to avoid climatic changes in the Amazon.
Daniele Peano, Deborah Hemming, Stefano Materia, Christine Delire, Yuanchao Fan, Emilie Joetzjer, Hanna Lee, Julia E. M. S. Nabel, Taejin Park, Philippe Peylin, David Wårlind, Andy Wiltshire, and Sönke Zaehle
Biogeosciences, 18, 2405–2428,Short summary
Global climate models are the scientist’s tools used for studying past, present, and future climate conditions. This work examines the ability of a group of our tools in reproducing and capturing the right timing and length of the season when plants show their green leaves. This season, indeed, is fundamental for CO2 exchanges between land, atmosphere, and climate. This work shows that discrepancies compared to observations remain, demanding further polishing of these tools.
Karun Pandit, Hamid Dashti, Andrew T. Hudak, Nancy F. Glenn, Alejandro N. Flores, and Douglas J. Shinneman
Biogeosciences, 18, 2027–2045,Short summary
A dynamic global vegetation model, Ecosystem Demography (EDv2.2), is used to understand spatiotemporal dynamics of a semi-arid shrub ecosystem under alternative fire regimes. Multi-decadal point simulations suggest shrub dominance for a non-fire scenario and a contrasting phase of shrub and C3 grass growth for a fire scenario. Regional gross primary productivity (GPP) simulations indicate moderate agreement with MODIS GPP and a GPP reduction in fire-affected areas before showing some recovery.
Martina Botter, Matthias Zeeman, Paolo Burlando, and Simone Fatichi
Biogeosciences, 18, 1917–1939,
Carlos A. Sierra, Susan E. Crow, Martin Heimann, Holger Metzler, and Ernst-Detlef Schulze
Biogeosciences, 18, 1029–1048,Short summary
The climate benefit of carbon sequestration (CBS) is a metric developed to quantify avoided warming by two separate processes: the amount of carbon drawdown from the atmosphere and the time this carbon is stored in a reservoir. This metric can be useful for quantifying the role of forests and soils for climate change mitigation and to better quantify the benefits of carbon removals by sinks.
Xiaoying Shi, Daniel M. Ricciuto, Peter E. Thornton, Xiaofeng Xu, Fengming Yuan, Richard J. Norby, Anthony P. Walker, Jeffrey M. Warren, Jiafu Mao, Paul J. Hanson, Lin Meng, David Weston, and Natalie A. Griffiths
Biogeosciences, 18, 467–486,Short summary
The Sphagnum mosses are the important species of a wetland ecosystem. To better represent the peatland ecosystem, we introduced the moss species to the land model component (ELM) of the Energy Exascale Earth System Model (E3SM) by developing water content dynamics and nonvascular photosynthetic processes for moss. We tested the model against field observations and used the model to make projections of the site's carbon cycle under warming and atmospheric CO2 concentration scenarios.
Peter Horvath, Hui Tang, Rune Halvorsen, Frode Stordal, Lena Merete Tallaksen, Terje Koren Berntsen, and Anders Bryn
Biogeosciences, 18, 95–112,Short summary
We evaluated the performance of three methods for representing vegetation cover. Remote sensing provided the best match to a reference dataset, closely followed by distribution modelling (DM), whereas the dynamic global vegetation model (DGVM) in CLM4.5BGCDV deviated strongly from the reference. Sensitivity tests show that use of threshold values for predictors identified by DM may improve DGVM performance. The results highlight the potential of using DM in the development of DGVMs.
Johan Arnqvist, Julia Freier, and Ebba Dellwik
Biogeosciences, 17, 5939–5952,Short summary
Data generated by airborne laser scans enable the characterization of surface vegetation for any application that might need it, such as forest management, modeling for numerical weather prediction, or wind energy estimation. In this work we present a new algorithm for calculating the vegetation density using data from airborne laser scans. The new routine is more robust than earlier methods, and an implementation in popular programming languages accompanies the article to support new users.
Bloom, A. A., Palmer, P. I., Fraser, A., Reay, D. S., and Frankenberg, C.: Large-Scale Controls of Methanogenesis Inferred from Methane and Gravity Spaceborne Data, Science, 327, 322–325, https://doi.org/10.1126/science.1175176, 2010.
Bloom, A. A., Palmer, P. I., Fraser, A., and Reay, D. S.: Seasonal variability of tropical wetland CH4 emissions: the role of the methanogen-available carbon pool, Biogeosciences, 9, 2821–2830, https://doi.org/10.5194/bg-9-2821-2012, 2012.
Bousquet, P., Ciais, P., Miller, J. B., Dlugokencky, E. J., Hauglustaine, D. A., Prigent, C., Van der Werf, G. R., Peylin, P., Brunke, E. G., Carouge, C., Langenfelds, R. L., Lathiere, J., Papa, F., Ramonet, M., Schmidt, M., Steele, L. P., Tyler, S. C., and White, J.: Contribution of anthropogenic and natural sources to atmospheric methane variability, Nature, 443, 439–443, https://doi.org/10.1038/Nature05132, 2006.
Butler, J. H., Daube, B. C., Dutton, G. S., Elkins, J. W., Hall, B. D., Hurst, D. F., King, D. B., Kling, E. S., Lafleur, B. G., Lind, J., Lovitz, S., Mondeel, D. J., Montzka, S. A., Moore, F. L., Nance, J. D., Neu, J. L., Romashkin, P. R., Sheffer, A., and Snible, W. J.: Halocarbons and other atmospheric trace species, CMDL Summary Report, edited by: Hompson, T. M., NOAA/US Department of Commerce, Boulder, Colorado, 115–135, 2004.
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